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LLMs and the Infrastructure of CSCW

Published: 14 October 2023 Publication History

Abstract

Large Language Models have made many completing many previously difficult to achieve artificial intelligence tasks approachable to more programmers and non-programmers alike. More recently, open-source versions of large language models and the creation of new finetuning methods have been developed. These models and their decvelopment models lead this panel to discuss how the infrastructure of CSCW will influence LLM model development. It will also discuss how open source LLMs might influence CSCW research, and how they might allow the CSCW community to have new input into trust, safety, and responsibility in AI.

References

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Minsuk Chang, Stefania Druga, Alex Fiannaca, Pedro Vergani, Chinmay Kulkarni, Carrie Cai, and Michael Terry. 2023. The Prompt Artists. arXiv preprint arXiv:2303.12253 (2023).
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Kevin Crowston, Qing Li, Kangning Wei, U Yeliz Eseryel, and James Howison. 2007. Self-organization of teams for free/libre open source software development. Information and software technology 49, 6 (2007), 564–575.
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Kevin Crowston, Kangning Wei, James Howison, and Andrea Wiggins. 2008. Free/Libre open-source software development: What we know and what we do not know. ACM Computing Surveys (CSUR) 44, 2 (2008), 1–35.
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Nadia Eghbal. 2016. Roads and bridges. The Unseen labor behind our digital infrastructure (2016).
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Sophie Jentzsch and Kristian Kersting. 2023. ChatGPT is fun, but it is not funny! Humor is still challenging Large Language Models. arXiv preprint arXiv:2306.04563 (2023).
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Eric Raymond. 1999. The cathedral and the bazaar. Knowledge, Technology & Policy 12, 3 (1999), 23–49.

Cited By

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  • (2024)GigSenseGigSenseAvances en Interacción Humano-Computadora10.47756/aihc.y9i1.1599:1(135-145)Online publication date: 30-Nov-2024
  • (2024)Proposal of User Interface Based on Heavy User Usage Analysis in LLM ServiceArchives of Design Research10.15187/adr.2024.08.37.4.28737:4(287-313)Online publication date: 31-Aug-2024

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Published In

cover image ACM Conferences
CSCW '23 Companion: Companion Publication of the 2023 Conference on Computer Supported Cooperative Work and Social Computing
October 2023
596 pages
ISBN:9798400701290
DOI:10.1145/3584931
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 October 2023

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Author Tags

  1. collaboration
  2. large language models
  3. open source

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  • Panel
  • Research
  • Refereed limited

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CSCW '23
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Overall Acceptance Rate 2,235 of 8,521 submissions, 26%

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Cited By

View all
  • (2024)GigSenseGigSenseAvances en Interacción Humano-Computadora10.47756/aihc.y9i1.1599:1(135-145)Online publication date: 30-Nov-2024
  • (2024)Proposal of User Interface Based on Heavy User Usage Analysis in LLM ServiceArchives of Design Research10.15187/adr.2024.08.37.4.28737:4(287-313)Online publication date: 31-Aug-2024

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